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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Variance : Journal of Statistics and Its Applications Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Intelligent Computing and Health Informatics (JICHI) Parameter: Journal of Statistics Journal Of Human And Education (JAHE) Journal of Learning Improvement and Lesson Study Journal of Data Insights Prosiding Seminar Nasional Unimus
Alwan Fadlurohman
Universitas Muhammadiyah Semarang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Generalized Space Time Autoregressive Modeling With Variable Exogenous (Gstar-X) (Case Study: Inflation In Six Cities Of Central Java) Alwan Fadlurohman; Tiani Wahyu Utami; Rochdi Wasono
Prosiding Seminar Nasional Unimus Vol 3 (2020): Optimalisasi Hasil Penelitian dan Pengabdian Masyarakat Menuju Kemandirian di Tengah P
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Inflasi adalah kecenderungan naiknya harga barang dan jasa yang berlangsung secara terus menerus. Inflasi merupakan data time series bulanan yang diduga juga dipengaruhi oleh unsur antar lokasi. Pemodelan untuk peramalan inflasi yang melibatkan unsur waktu dan lokasi (spatio temporal) dapat menggunakan metode Generalized Space Time Autoregressive (GSTAR). Untuk menambah akurasi dalam peramalan, model GSTAR dikembangkan menjadi model GSTARX dengan melibatkan variabel eksogen. Variabel eksogen yang digunakan dalam pemodelan GSTARX untuk peramalan Inflasi ini adalah variasi kalender idul fitri yaitu inflasi pada bulan di hari raya idul fitri. Studi kasus dalam pemodelan GSTARX ini diterapkan untuk peramalan inflasi enam kota Survei Biaya Hidup (SBH) di Jawa Tengah yaitu Cilacap, Purwokerto, Semarang, Kudus, Magelang dan Surakarta. Tujuan penelitian ini adalah ingin mendapatkan model GSTARX yang terbaik untuk pemodelan inflasi enam kota SBH diJawa Tengah. Didapatkan 2 (dua) model GSTARX dengan nilai RMSE masing-masing adalah model dengan bobot lokasi seragam memiliki nilai RMSE sebesar 0,6108, model dengan bobot lokasi invers jarak memiliki nilai RMSE sebesar 0,6124. Dapat disimpulkan bahwa model GSTARX menggunakan bobot lokasi seragam adalah model terbaik. Kata Kunci : GSTAR, GSTARX, Inflasi, Jawa Tengah, Survei Biaya Hidup.
Pengelompokkan Provinsi di Indonesia Berdasarkan Indikator Perumahan dan Kesehatan Lingkungan Menggunakan Metode KMedoids Alwan Fadlurohman; Indah Manfaati Nur
Prosiding Seminar Nasional Unimus Vol 6 (2023): Membangun Tatanan Sosial di Era Revolusi Industri 4.0 dalam Menunjang Pencapaian Susta
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Indikator perumahan dan kesehatan lingkungan merupakan salah satu indikator yang sangat penting dalamupaya mewujudkan tujuan dari Tujuan Pembangunan Berkelanjutan (TPB). Kondisi perumahan dankesehatan lingkungan di setiap provinsi di Indonesia berbeda-beda, oleh karena itu dalam melakukan prioritaspeningkatan masalah perumahan dan kesehatan lingkungan juga berbeda. Tujuan atas penelitian ini guna mengklasifikan provinsi di Indonesia atas dasar indikator perumahan dan kesehatan lingkungan untukmengetahui tinggi rendahnya kualitas perumahan dan lingkungan di setiap provinsi. Sehingga, hasil penelitiandengan harap mampu membantu pemerintah mengoptimalkan upaya kesehatan lingkungan. Pengelompokanprovinsi dilakukan dengan metode K-Medoids yang memiliki kelebihan robust terhadap data yangmengandung pencilan. Ukuran kemiripan objek dihitung dengan menggunakan metode jarak Euclidean.Sementara itu, pemilihan jumlah cluster terbaik dilakukan menggunakan indeks silhouette yang menghasilkan2 cluster, dimana pada cluster 1 didapatkan 29 provinsi dengan nilai rata-rata indikator perumahan dankesehatan lingkungan (X2, X4, X5, X6, X7, dan X10) rendah. Lalu cluster 1 didapatkan 5 provinsi dengan nilairata-rata indikator perumahan dan kesehatan lingkungan (X2, X4, X5, X6, X7, dan X10) tinggi. Kata Kunci: Dampak Perkotaan, Pencilan, Pengelompokkan, Sanitasi.
Scientific Article "Lesson Study": Portrait of Improving the Teacher Learning Quality Winaryati, Eny; Iksan, Zanaton Haji; Rauf, Rose Amnah Abd; Sugiharto, Prasetyawan Aji; Fadlurohman, Alwan; Yusrin, Yusrin; Maharani, Endang Tri Wahyuni
Journal of Learning Improvement and Lesson Study Vol 4 No 1 (2024): JLILS (June Edition)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jlils.v4i1.87

Abstract

The aim of this research is: photographing the teacher's lesson study learning process, as well as evaluate information findings resulting from LS scientific article preparation activities. This research is based on a phenomenological approach, which focuses more on phenomena that are felt, obtained, responded to, perceived by subjects (humans) towards objects (LS scientific articles) written by teachers. The results of LS teacher's writing of scientific articles, are the result of narrating the implementation of lesson study, producing several findings, namely: firstly, they have writing skills to narrate teaching experiences. Some teachers are doing this skill for the first time. Second, photographing LS activities to narrate in articles, provides an interesting and challenging experience. Third, being able to present learning activities to be published as work results is a source of pride for teachers. Fourth, considering that LS activities are personal experiences, conveying them in written form is like telling a story. Fifth, encourage collaborative writing, as a result of collaborative LS experience, and the results of collaborative work. Sixth, preparing LS articles encourages teachers to look for lots of references, so that good LS articles are produced. Seventh, articles that are prepared collaboratively produce rich ideas, because they create an exchange of ideas to produce better articles. Eighth, there is a correlation between the lesson study stages, the problems that will be solved through learning, and the learning strategies carried out by the teacher. Ninth, LS activities will become teacher best practices in learning, when written in a scientific article. This LS scientific article expands information on the success or best practice of learning for many people. Tenth, the quality of the scientific articles produced is a portrait of the mastery of the lesson study that has been carried out. Suggestion: it needs to be used as a habit for lesson study activities which have an impact on writing scientific articles. The aim is to improve writing skills for teachers, while encouraging collaborative work as a habituation process, as well as training that learning experiences can become best practices that can be disseminated as more useful information.
Integration of GSTAR-X and Uniform location weights methods for forecasting Inflation Survey of Living Costs in Central Java Fadlurrohman, Alwan
Journal of Intelligent Computing & Health Informatics Vol 1, No 1 (2020): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i1.5583

Abstract

Inflation is a tendency to increase prices of goods and services that take place continuously. Inflation is a monthly time series data that is thought to be influenced by location elements. Modeling for inflation forecasting that involves time and location (spatio temporal) can use the Generalized Space Time Autoregressive (GSTAR) method. To increase accuracy in modeling and forecasting, the GSTAR model was developed into the GSTARX model by involving exogenous variables. Exogenous Variavel used in GSTARX modeling for forecasting Inflation is a variation of the Eid calendar. This GSTARX modeling is applied for inflation forecasting in six cities Cost of Living Survey (SBH) in Central Java, namely Cilacap, Purwokerto, Semarang, Kudus, Magelang and Surakarta. The purpose of this study is to get the best GSTARX model for inflation forecasting for six SBH cities in Central Java. The selection of the best model from the GSTARX method is seen with the smallest RMSE value of each model. Obtained that the GSTARX model with uniform weights is the best model because it has a smaller RMSE compared to the GSTARX model with inverse distance weights, the RMSE values are 0.6122 and 0.6137, respectively. It can be concluded that the GSTARX method with Uniform weighting can provide better performance and can be used to predict the inflation of the six SBH cities in Central Java in the next 12 periods.
Klasifikasi Dataset Diabetes menggunakan Algoritma K-Nearest Neighbors Fitri Diana Musa; M. Al Haris; Dannu Purwanto; Saeful Amri; Alwan Fadlurohman; Ariska Fitriyana Ningrum
Journal of Data Insights Vol 2 No 1 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

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Abstract

Data mining merupakan suatu metode yang baik untuk menangani data skala besar. Performasi menjadi penting dalam metode data mining. Salah satu metode yang memiliki performasi terbaik adalah K-Nearest Neighbor (KNN). Artikel ini membahas terkait performasi K-NN. Data yang digunakan pada penelitian ini adalah Diabetes. Data dibagi menjadi 80% data trainingdan 20% data testing. Dengan menggunakan 11 tetangga terdekat, model menghasilkan akurasi sebesar 0.765625. Angka ini mencerminkan kinerja yang baik. Metrik kritis termasuk akurasi sebesar 0.77, presisi sebesar 0.80, dan recall sebesar 0.85. Hasil ini menunjukkan bahwa model KNN memiliki potensi untuk mengklasifikasikan pasien diabetes dengan akurasi yang baik.
Fuzzy Gustafson Kessel for Infrastructure Development Strategy in South Sumatra Province: Fuzzy Gustafson Kessel Untuk Strategi Pembangunan Infrastruktur Di Provinsi Sumatera Selatan Ariska Fitriyana Ningrum; Oktaviana Rahma Dhani; Febi Anggun Lestari; Zahra Aura Hisani; Alwan Fadlurohman
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.650

Abstract

Infrastructure development is a strategic element in improving public services and economic growth. South Sumatra Province, with its large economic potential, faces challenges in managing efficient and sustainable infrastructure development. This research aims to apply the Fuzzy Gustafson Kessel (FGK) method in decision making related to infrastructure development in South Sumatra Province. FGK combines fuzzy logic with Gustafson Kessel clustering algorithm to handle uncertainty and data variation from various stakeholders. The data used in this study includes population and geographic census data from the Central Bureau of Statistics of South Sumatra Province in 2023, with five indicators: population, area, population growth rate, population density, and poverty rate. The results show that South Sumatra is divided into three main clusters based on its infrastructure and demographic characteristics. This clustering is expected to improve the effectiveness and efficiency of infrastructure development decision-making, provide more appropriate policy recommendations, and potentially be applied in other regions with similar challenges.
OPTIMALKAN PEMAHAMAN DATA DENGAN DASHBOARD MELALUI PELATIHAN VISUALISASI DATA UNTUK SISWA SMA N 1 KEMBANG JEPARA Alwan Fadlurohman; Fatkhurokhman Fauzi; Febi Anggun Lestari; Albertus Dion Sarah
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 5 (2024): Vol. 5 No. 5 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i5.34893

Abstract

Seiring dengan kemajuan teknologi informasi dan memasuki era revolusi industri 4.0, pemanfaatan teknologi dalam aktivitas manusia semakin meningkat. Data kini menjadi aset berharga, dan kemampuan dalam mengumpulkan, menganalisis, serta menginterpretasi data telah menjadi keterampilan krusial dalam dunia kerja dan pendidikan. Pendidikan memainkan peran penting dalam mempersiapkan generasi mendatang untuk menghadapi tantangan global yang semakin kompleks. Di SMAN 1 Kembang Kabupaten Jepara, terdapat beberapa masalah utama, yaitu keterbatasan akses dan pemahaman siswa mengenai data, kurangnya pengalaman dalam visualisasi data, dan minimnya pemahaman tentang manfaat visualisasi data. Program pelatihan ini bertujuan untuk meningkatkan pemahaman siswa mengenai data dan teknik visualisasi melalui penyampaian materi konseptual tentang konsep data dan visualisasi, penggunaan Google Data Studio, dan pembuatan dashboard visualisasi. Pelaksanaan PKM ini menggunakan metode interaktif dan demontrasi kepada siswa kelas 11 SMAN 1 Kembang sebanyak 20 orang. Hasil PKM menunjukkan bahwa siswa mampu meningkatkan pemahaman mereka tentang konsep dasar data, jenis-jenis data, dan pentingnya visualisasi data. Siswa juga menunjukkan kemajuan yang baik dalam keterampilan teknis terkait penggunaan Google Data Studio untuk mengolah dan memvisualisasikan data. Mereka berhasil menerapkan berbagai fitur untuk menyusun grafik, diagram, dan visualisasi lain yang sesuai dengan data yang diberikan. Hasil visualisasi ini memperlihatkan kemampuan siswa dalam menyajikan data dengan cara yang informatif dan menarik.
CLASSIFICATION OF MYPERTAMINA APP REVIEWS USING SUPPORT VECTOR MACHINE Fadlurohman, Alwan; Yunanita, Novia; Rohim, Febrian Hikmah Nur; Wardani, Amelia Kusuma; Ningrum, Ariska Fitriyana
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page223-228

Abstract

Indonesia is rich in natural resources, including oil and gas, and it manages these strategic assets through state-owned enterprises, one of which is PT Pertamina. Pertamina is responsible for domestic fuel production, distribution, and price stabilization. To improve efficiency and transparency, Pertamina developed the MyPertamina application that enables cashless fuel purchases, stock monitoring, and up-to-date price information. The application aims to streamline distribution and control fuel prices, thus helping to stabilize the cost of goods and services. MyPertamina also ensures subsidized fuel distribution is more effective and targeted by identifying and verifying subsidy recipients, reducing the potential for abuse. A sentimental analysis of subsidized fuel user reviews using this application is needed to understand the public's views. This research uses the Support Vector Machine (SVM) method to analyze the sentiment of MyPertamina app reviews. This research produced a stable model. Out of 200 reviews, 190 were negative, and nine were positive, with an SVM model accuracy of 97%. Wordcloud visualization shows the words that appear frequently in each sentiment. Positive reviews appreciated the photo verification feature, easy payment, and good service. Negative reviews included verification difficulty, app error, and feature failure.
SOCIAL VULNERABILITY ANALYSIS IN CENTRAL JAVA WITH K-MEDOIDS ALGORITHM Fadlurohman, Alwan; Ayu Nur Roosyidah, Nila; Amalia Annisa, Nafida
Parameter: Journal of Statistics Vol. 4 No. 2 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i2.17131

Abstract

To address the limitations of the Social Vulnerability Index (SoVI) in only providing a general overview without pinpointing areas of social vulnerability, a correlational approach paired with a clustering method can be applied. This approach helps in identifying dominant factors and pinpointing socially vulnerable districts or cities in Central Java. The study employs the K-Medoids algorithm, which is advantageous when dealing with outliers in the dataset. Three different distance measures are considered: Euclidean, Manhattan, and Minkowski distances, to identify the optimal clustering of social vulnerability. The evaluation of the best cluster is conducted using the Davies-Bouldin Index, a metric for validating clustering models by averaging the similarity of each cluster to its most similar counterpart. Findings indicate that using the K-Medoids algorithm with Manhattan distance yields the most effective clustering, resulting in two distinct clusters. Cluster 1, comprising 25 districts/cities, is identified as the most vulnerable to natural disasters and challenges in education, demography, economy, and health. Meanwhile, Cluster 2, encompassing 10 districts/cities, includes urban areas with the highest social vulnerability, notably in the proportion of rental housing.
Prediksi Jumlah Penumpang Di Bandara Nasional Ahmad Yani Semarang Menggunakan Holt Winter’s Exponential Smoothing (HWES) Gautama, Rahmad Putra; Fadlurohman, Alwan; Arum, Prizka Rismawati; Dhani, Oktaviana Rahma
Prosiding Seminar Nasional Unimus Vol 7 (2024): Transformasi Teknologi Menuju Indonesia Sehat dan Pencapaian Sustainable Development G
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Pesawat terbang memberikan kenyamanan dan kecepatan bagi penggunanya terutama bagi mereka yangmemiliki keterbatasan waktu. Peningkatan jumlah penumpang terus terjadi beberapa bulan ini, sehinggadibutuhkan suatu peramalan dalam mengambil keputusan untuk memprediksi jumlah penumpang gunamemaksimalkan kinerja yang ada. Karena metode Holt Winters Exponential Smoothing tidak sangat akuratdan sesuai dengan asumsi awal dari pola data penelitian, metode ini digunakan. Studi ini bertujuan untukmenggunakan metode Holt Winters Exponential Smoothing untuk meramalkan jumlah penumpang pesawatdi Bandara Nasional Ahmad Yani Semarang. Hasil analisis menunjukkan bahwa metode ini memiliki nilaiMAPE sebesar 13,98%, yang menunjukkan bahwa metode ini adalah pilihan yang baik dan tepat untukmeramalkan jumlah penumpang pesawat di Bandara Nasional Ahmad Yani Semarang. Kata Kunci : Holt Winters Exponential Smoothing, Mape, Penumpang, Peramalan
Co-Authors Albertus Dion Sarah Amalia Annisa, Nafida Amri, Saeful Amrullah, Setiawan Ariska Fitriyana Ningrum Ayu Nur Roosyidah, Nila Dannu Purwanto Dhani, Oktaviana Rahma Endang Tri Wahyuni Maharani Eny Winaryati Fatkhurokhman Fauzi Febi Anggun Lestari Febi Anggun Lestari Fitri Diana Musa Gautama, Rahmad Putra Ihsan Fathoni Amri Iksan, Zanaton Haji Indah Manfaati Nur M. Al Haris Oktaviana Rahma Dhani Prasetyawan Aji Sugiharto Prizka Rismawati Arum Rauf, Rose Amnah Abd Rochdi Wasono Rohim, Febrian Hikmah Nur Roosyidah, Nila Ayu Nur Tiani Wahyu Utami Wardani, Amelia Kusuma Yunanita, Novia Yusrin, Yusrin Zahra Aura Hisani